PluginBench
Skill
Review
Audit score 70

connections-optimizer

affaan-m/ecc

Reorganize your X and LinkedIn network with review-first pruning, smart recommendations, and warm outreach in your voice.

What is connections-optimizer?

Connections Optimizer helps you clean up and strategically grow your social graph on X and LinkedIn. It scores your current follows for relevance to your priorities, surfaces pruning candidates with confidence levels, recommends high-value accounts to follow, and drafts personalized outreach—all review-gated before any action.

  • Score and rank your X following and LinkedIn connections by relevance, reciprocity, engagement, and bridge value
  • Generate review-first prune queues with explicit reasons and confidence levels for each candidate
  • Identify add/follow targets aligned to your current priorities with warm-path detection
  • Draft channel-specific outreach (X DM, LinkedIn message, or email) in your authentic voice
  • Distinguish between one-way follows (prune-friendly) and mutual connections (review-gated)
  • Run in three modes: light-pass, default, or aggressive based on your cleanup intensity

How to install connections-optimizer

npx skills add null --skill connections-optimizer
Prerequisites
  • X API access (preferred) or browser control for X analysis
  • LinkedIn API access (preferred) or browser control for LinkedIn analysis
  • Apple Mail or Mail.app for email draft generation
  • Optional: lead-intelligence, social-graph-ranker, and brand-voice skills for enhanced recommendations and voice matching
Claude Code
Cursor
Windsurf
Cline

How to use connections-optimizer

  1. 1.Specify your current priorities, target roles/industries, and do-not-touch list
  2. 2.Select platforms (X, LinkedIn, or both) and pruning mode (light-pass, default, or aggressive)
  3. 3.Let the skill pull your current following/connection inventory and score candidates
  4. 4.Review the generated report with prune queue, keep list, and add/follow targets
  5. 5.Approve drafts for warm outreach before any messages or connection changes are sent
  6. 6.Apply approved actions or iterate on recommendations

Use cases

Good for
  • Clean up a bloated X following list while protecting mutuals and high-value bridges
  • Rebalance your LinkedIn network toward current work priorities and role-relevant connections
  • Identify who to follow next in your industry or ecosystem with warm introductions ready
  • Draft personalized reconnection messages to dormant but valuable contacts
  • Audit your social graph for signal quality and remove low-engagement or off-priority accounts
Who it's for
  • Professionals managing large X or LinkedIn networks
  • Founders and operators rebalancing their graph around new priorities
  • Sales and business development roles seeking warm-path outreach
  • Anyone wanting to replace one-way prospecting lists with strategic network design

connections-optimizer FAQ

Will this automatically unfollow or remove connections?

No. The skill is review-first by default. It generates ranked action plans and drafts, but never auto-sends messages or applies changes without your approval.

What's the difference between light-pass, default, and aggressive modes?

Light-pass prunes only high-confidence low-value one-way follows; default balances pruning with expansion; aggressive has lower tolerance for stale follows but still requires review before applying.

Can I protect specific accounts from being pruned?

Yes. You provide a do-not-touch list upfront, and the skill will never recommend those accounts for removal.

What signals does the skill use to score accounts?

Positive signals include reciprocity, recent activity, alignment to your priorities, bridge value, and real engagement. Negative signals include abandoned accounts, stale one-way follows, off-priority topics, and non-response.

Which channel does it use for outreach?

The skill matches the right channel based on warmth and context: X DM for fast social touches, LinkedIn message for professional adjacency, or Apple Mail for higher-context intros. It drafts in your voice and never sends automatically.

Full instructions (SKILL.md)

Source of truth, from affaan-m/ecc.


name: connections-optimizer description: Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships. metadata: origin: ECC

Connections Optimizer

Reorganize the user's network instead of treating outbound as a one-way prospecting list.

This skill handles:

  • X following cleanup and expansion
  • LinkedIn follow and connection analysis
  • review-first prune queues
  • add and follow recommendations
  • warm-path identification
  • Apple Mail, X DM, and LinkedIn draft generation in the user's real voice

When to Activate

  • the user wants to prune their X following
  • the user wants to rebalance who they follow or stay connected to
  • the user says "clean up my network", "who should I unfollow", "who should I follow", "who should I reconnect with"
  • outreach quality depends on network structure, not just cold list generation

Required Inputs

Collect or infer:

  • current priorities and active work
  • target roles, industries, geos, or ecosystems
  • platform selection: X, LinkedIn, or both
  • do-not-touch list
  • mode: light-pass, default, or aggressive

If the user does not specify a mode, use default.

Tool Requirements

Preferred

  • x-api for X graph inspection and recent activity
  • lead-intelligence for target discovery and warm-path ranking
  • social-graph-ranker when the user wants bridge value scored independently of the broader lead workflow
  • Exa / deep research for person and company enrichment
  • brand-voice before drafting outbound

Fallbacks

  • browser control for LinkedIn analysis and drafting
  • browser control for X if API coverage is constrained
  • Apple Mail or Mail.app drafting via desktop automation when email is the right channel

Safety Defaults

  • default is review-first, never blind auto-pruning
  • X: prune only accounts the user follows, never followers
  • LinkedIn: treat 1st-degree connection removal as manual-review-first
  • do not auto-send DMs, invites, or emails
  • emit a ranked action plan and drafts before any apply step

Platform Rules

X

  • mutuals are stickier than one-way follows
  • non-follow-backs can be pruned more aggressively
  • heavily inactive or disappeared accounts should surface quickly
  • engagement, signal quality, and bridge value matter more than raw follower count

LinkedIn

  • API-first if the user actually has LinkedIn API access
  • browser workflow must work when API access is missing
  • distinguish outbound follows from accepted 1st-degree connections
  • outbound follows can be pruned more freely
  • accepted 1st-degree connections should default to review, not auto-remove

Modes

light-pass

  • prune only high-confidence low-value one-way follows
  • surface the rest for review
  • generate a small add/follow list

default

  • balanced prune queue
  • balanced keep list
  • ranked add/follow queue
  • draft warm intros or direct outreach where useful

aggressive

  • larger prune queue
  • lower tolerance for stale non-follow-backs
  • still review-gated before apply

Scoring Model

Use these positive signals:

  • reciprocity
  • recent activity
  • alignment to current priorities
  • network bridge value
  • role relevance
  • real engagement history
  • recent presence and responsiveness

Use these negative signals:

  • disappeared or abandoned account
  • stale one-way follow
  • off-priority topic cluster
  • low-value noise
  • repeated non-response
  • no follow-back when many better replacements exist

Mutuals and real warm-path bridges should be penalized less aggressively than one-way follows.

Workflow

  1. Capture priorities, do-not-touch constraints, and selected platforms.
  2. Pull the current following / connection inventory.
  3. Score prune candidates with explicit reasons.
  4. Score keep candidates with explicit reasons.
  5. Use lead-intelligence plus research surfaces to rank expansion candidates.
  6. Match the right channel:
    • X DM for warm, fast social touch points
    • LinkedIn message for professional graph adjacency
    • Apple Mail draft for higher-context intros or outreach
  7. Run brand-voice before drafting messages.
  8. Return a review pack before any apply step.

Review Pack Format

CONNECTIONS OPTIMIZER REPORT
============================

Mode:
Platforms:
Priority Set:

Prune Queue
- handle / profile
  reason:
  confidence:
  action:

Review Queue
- handle / profile
  reason:
  risk:

Keep / Protect
- handle / profile
  bridge value:

Add / Follow Targets
- person
  why now:
  warm path:
  preferred channel:

Drafts
- X DM:
- LinkedIn:
- Apple Mail:

Outbound Rules

  • Default email path is Apple Mail / Mail.app draft creation.
  • Do not send automatically.
  • Choose the channel based on warmth, relevance, and context depth.
  • Do not force a DM when an email or no outreach is the right move.
  • Drafts should sound like the user, not like automated sales copy.

Related Skills

  • brand-voice for the reusable voice profile
  • social-graph-ranker for the standalone bridge-scoring and warm-path math
  • lead-intelligence for weighted target and warm-path discovery
  • x-api for X graph access, drafting, and optional apply flows
  • content-engine when the user also wants public launch content around network moves